We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
基于时间序列分析的悬浮红细胞临床需求预测模型研究.
- Authors
彭荣荣; 刘芸男; 杨冬燕; 王含柔; 赵明烽; 杨小丽
- Abstract
Objective To explore the clinical demand prediction model of suspended red blood cells using a time series analysis,and to provide a scientific basis for the collection and storage of blood resources. Methods Auto regressive integrated moving average( ARIMA) models were established to predict the ABO blood type usage and the total usage of suspended red blood cells that would be required monthly at Wanzhou Central Blood Station,Chongqing,China. These models were based on the actual usage required between January 2006 and June 2016. The models were used to predict the ABO blood type usage and the total usage of suspended red blood cells monthly from July to December 2016 to verify the prediction effect of the models. Results All the optimal models passed the autocorrelation function,the partial autocorrelation function of the residual sequence and the Ljung-Box Q test. The dynamic trends of the predicted values were generally consistent with the actual clinical usage of suspended red blood cells in the same period,with a small mean relative error and high prediction accuracy. Conclusion Optimal models better fit the clinical usage trend of suspended red blood cells in a time series. The ARIMA models can be used to predict the clinical usage of suspended red blood cells.
- Publication
Journal of China Medical University, 2020, Vol 49, Issue 6, p532
- ISSN
0258-4646
- Publication type
Article
- DOI
10.12007/jissn0258-4646.2020.06.012